Cognitive Radio Networks

LTE networks are commonplace nowadays; however, comparatively little is known about where (and why) they are deployed, and the demand they serve. We shed some light on these issues through large-scale, crowd-sourced measurement. Our data, collected by users of the WeFi app, spans multiple operators and multiple cities, allowing us to observe a wide variety of deployment patterns. Surprisingly, we find that LTE is frequently used to improve the coverage of network rather than the capacity thereof, and that no evidence shows that video traffic be a primary driver for its deployment. Our insights suggest that such factors as pre-existing networks and commercial policies have a deeper impact on deployment decisions than purely technical considerations.

Machine Learning approaches such as Reinforcement Learning (RL) can be used to solve problems such as spectrum sensing and channel allocation in the cognitive radio domain. These approaches have been applied to other similiar domains such as in mobile telephone networks and have shown greater performance than the static channel allocation schemes used. The objective of this research is to use an RL technique known as Q-Learning to provide a possible solution for allocating channels in a wireless network containing independent cognitive nodes. Q-Learning is an attractive algorithm for such a problem because of the low computational demands per iteration. Many or the current proposed techniques suggest using a negotiation policy between two nodes to decide on which channel each may use, however a considerable problem with this is the overhead involved in the negotiation involved between the nodes. This paper suggests an approach where each node acts as an individual independant node, with virtually no collaboration with the other nodes. Results have shown that using such a technique gives fast convergence on an optimal solution when correct rates are chosen. It has also shown that the algorithm is very scalable, in that as the network grows, the state-action space does not grow sufficiently to cause major memory or computational demands.

Power Electronics applications have long employed switching techniques including pulse-width and pulse-density modulation. Because semiconductor technology is growing so quickly, blocks in the radio architecture may benefit from similar strategies. The implementation of a class-D power amplifier for radiofrequency applications in low-GHz frequency bands is described in this paper. We explain why linear amplitude modulation of a nominally nonlinear switching power amplifier is desirable through the use of pulse-density modulation (PDM). With a peak efficiency of 43.5% at 1.95GHz and an output power of up to 20dBm, the amplifier achieves linearity appropriate for wideband wireless standards. The system produces amplitude-modulated waveforms with an envelope bandwidth of up to 20MHz, proving the applicability of this method for contemporary communication standards.

Cognitive radio networks provide an important function in the efficient use of the radio spectrum. Therefore, dedicated cognitive radio ad hoc networks (CRAHNs) are expected to improve communication performance in a multihop network that requires a dedicated routing protocol that considers the dynamic mobility of secondary user nodes on the basis of the random availability of primary node channels. To enhance routing in the CRAHNs environment, in this paper, a novel Hybrid Cooperative Spectrum Structured (HCSS) approach that combines cooperative spectrum sensing and spectrum-aware routing protocols can be effective in appropriate decision making for routing packets in such a network. This approach integrates the strengths of Spectrum-Aware Semi-Structured Routing (SSR) and Spectrum-Aware Routing Protocol (SARP) to enable adaptive and efficient routing in dynamic CRAHN environments. The results showed that the proposed HCSS routing protocol increased the user demand while ensuring the quality of service (QoS) requirements by achieving an average throughput of 5164.55 Kbps, exceeding the SARP and SSR, which recorded 4585.56 Kbps and 4194.66 Kbps, respectively. The PDR for HCSS was 98.77%, which was significantly higher than that for SARP (95.60%), and the SSR was 90.15%, indicating better reliable connectivity in delivering packets to their final destinations.

Cognitive radio networks are characterized by their ability to adapt to dynamic spectrum variables and network environment conditions. Reliable communication in cognitive radio networks is essential to achieve the most efficient use of spectrum and flexible communication between the different network components. In this paper, a novel Hybrid Cognitive Adaptive Routing Algorithm (HCARA) is proposed for the routing process in cognitive radio networks. HCARA aims to achieve the highest quality of service while minimizing delay during the transmission and reception of data between secondary nodes in the network. The communication path between the nodes is chosen dynamically in a reliable and efficient manner depending on the channel conditions, traffic load, and network topology, as the proposed protocol is based on multiple routing metrics during the decision-making process, including throughput, packet delivery ratio and delay through the round trip of the data transmission. The proposed HCARA was chosen to address limitations in existing routing protocols specifically the Clustering-Based Routing Protocol (CRP) and Multimetric Routing Protocol with Service Differentiation (MRSED) in terms of throughput and reliability, as evidenced by HCARA's superior performance metrics: an average throughput of 14.64 Mbps, surpassing CRP and MRSED, which recorded 11.86 Mbps and 12.92 Mbps respectively. PDR for HCARA was measured at 98.51%, significantly higher than CRP's 89.24% and MRSED's 94.81%, indicating better reliability in delivering packets to their intended destinations.

In this paper, we consider an advanced wireless user, called primary-secondary user (PSU) who is capable of harvesting renewable energy and connecting to both the primary network and cognitive radio networks simultaneously. Recently, energy harvesting has received a great deal of attention from the research community and is a promising approach for maintaining long lifetime of users. On the other hand, the cognitive radio function allows the wireless user to access other primary networks in an opportunistic manner as secondary users in order to receive more throughput in the current time slot. Subsequently, in the paper we propose the channel access policy for a PSU with consideration of the energy harvesting, based on a Partially Observable Markov decision process (POMDP) in which the optimal action from the action set will be selected to maximize expected long-term throughput. The simulation results show that the proposed POMDP-based channel access scheme improves the throughput of PSU, but it requires more computations to make an action decision regarding channel access.

In this letter, we obtain the stable throughput region for a cognitive relaying scheme with a finite relaying buffer and imperfect sensing. The analysis investigates the effect of the secondary user's finite relaying capabilities under different scenarios of primary, secondary and relaying links outages. Furthermore, we demonstrate the effect of miss detection and false alarm probabilities on the achievable throughput for the primary and secondary users.

Modern electronic warfare has evolved far beyond the traditional confines of the physical battlefield, extending its reach into the electromagnetic spectrum, digital networks, and even the realm of human cognitive perception. In this new era, the concept of "reverse neo-cortical electronic warfare" emerges as a hypothetical yet plausible scenario where combat is no longer confined to the interception of signals but extends to the manipulation of artificial cognitive processes and neural networks. This form of warfare leverages advanced technologies to exploit vulnerabilities in both human and machine decision-making systems, creating a complex and dynamic battlefield where traditional strategies and resources may no longer suffice. In this context, survival and success depend on three key principles: creativity, decentralization, and accessibility. Creativity is essential to devise innovative solutions that can outmaneuver technologically superior adversaries. Decentralization ensures resilience by distributing resources and decision-making across networks, eliminating single points of failure. Accessibility, achieved through low-cost and open-source technologies, empowers individuals and communities to participate in the defense against electronic threats without relying on expensive or proprietary systems. This essay proposes a framework for resistance in the age of reverse neocortical electronic warfare, focusing on the development of low-cost devices and artifacts that enable individuals and communities to resist, adapt, and counterattack. These devices include: • The Dynamic Spectrum Cognitive Radio (DSCR), which uses AIdriven frequency hopping to evade jamming and maintain communication in congested environments. • The Tactical Mesh Communication Network (TMCN), a decentralized and secure communication system that operates independently of traditional infrastructure.

A Mobile Ad-Hoc Network (MANET) consists of a number of mobile nodes that are connected dynamically without any infrastructure. In this network type, the use of the clustering technique significantly reduces the routing traffic that occurs during the routing process. Clustering is used to divide an ad-hoc network into small sets of nodes, where each cluster consist of a cluster head, ordinary nodes and gateway nodes. Clustering can be used for the effective utilization of resources for large ad-hoc networks. This paper measures the impact of using clustering strategy in MANET and how this strategy can enhance the performance of this network, and resulted in increasing the calculated quality parameters, like throughput, packet delivery ratio, end-to-end delay and normalized control overhead. This study produced a simulation for Low-Energy Adaptive Clustering Hierarchy (LEACH) which is considered one of the clustering based routing protocols. A comparison is done between LEACH with the other types of routing protocols such as AODV, DSDV and OLSR which are considered non-clustering routing protocol. Conclusion and discussion of the simulation results have demonstrated the importance and effect of using clustering in MANETs.

This paper addresses the flight dynamics modelling and analysis as well as the basic stabilization study of the SAGITTA Demonstrator in early design stages. A focus is to support the process of control effectors specification with trim, maneuvering and stabilization requirements to reduce the count of design iterations. The SAGITTA Demonstrator, flying testbed of the open innovation project SAGITTA, represents a flying wing configuration, which is characterized by (static) lateral-directional instability in regions of its flight envelope. Regarding the trim curve analysis, it is common practice to investigate the target flight envelope for regions where it is not possible to trim the aircraft due to limited control power. Without the control effectors being specified, the evaluation of the trimmability has to be replaced by the derivation of least control moment needs ensuring trimmability. Besides the mere ability to trim the aircraft in different mission relevant flight conditions, every aircraft has to meet requirements regarding its dynamic charcteristics. For manned aircraft, these requirements are usually derived from the need to guarantee a certain level of flying and handling qualities. In case of autonomous unmanned systems, handling qualities are less relevant but instead requirements driven by the designated mission and hence the maneuver performance come to the fore. In this context, a lower bound for the needed roll control effectiveness to achieve a desired steady state bank angle within a given time will be derived analytically. Typically, an assessment of the stabilization capability is conducted in case of an inherent unstable design by means of nonlinear simulation after control effectors and control laws have (preliminary) been specified. This bears the risk of an undesirable high count of design iterations until an adequate trade-off between the degree of instability and the superior design objectives (as performance, low observability, etc.) will be achieved. In contrast to that approach, a basic stabilization study is accomplished prior to the specification of control effectors or control laws. This study applies a novel methodology balancing the destabilizing moment build-up due to a sideslip disturbance independently against the counteracting control moment development in terms of a worst case approximation of the real effective moment build-up of a controlled aircraft.

The exponential growth and proliferation of wireless devices for different wireless applications have led to the emergence of cognitive radio network (CRN) for optimal utilization of scarce spectrum resources. However, these resources have grossly been underutilized due to the inaccurate spectrum predictions. Existing spectrum occupancy and prediction techniques which rely on 2-state hidden Markov model (HMM) results in false alarm or missed detection caused by noisy or incomplete observable effects. In this paper, a 3state HMM spectrum occupancy and prediction technique in CRNs is proposed. The transmission, emission and initial state probabilities of the proposed 3-state HMM parameters were derived based on the three canonical problems associated with HMM. The evaluation, decoding and learning problems were solved using Forward algorithm, Viterbi algorithm and the Baum-Welch algorithm, respectively. The performance of the proposed 3-state HMM spectrum prediction technique was evaluated using prediction accuracy, probability of detection and spectrum utilization efficiency. The simulation results obtained revealed that the 3-state HMM outperformed the 2-state HMM spectrum prediction technique by 24.1% in prediction accuracy.

This paper investigated frequency sharing between primary TV systems (channels 32 and 49) and Emergency Communication Networks (ECNs). The networks to be implemented in the Osogbo axis of Osun State function on a secondary geographical basis, creating no harm to the original licensed primary TV viewers. A minimum separation distance of 41 dB was suggested as the protected contour for the UHF spectrum to oversee the protection of primary TV users for the UHF bands under consideration. The effects of changing the secondary systems' transmitting power, transmission frequency, and antenna height on the service coverage distance were also explored. The performance of the UHF band was evaluated when it was utilized for secondary transmission at both low and high transmitting powers, with the performance criterion being percentage coverage distance. This work complies with the International Telecommunication Union-Radio sector (ITU-R) recommendations of 16 dB for signal-to-noise ratio and 41 dB for signal strength. It can also be deduced from the result that when the transmission power of ECN devices is raised from 40 mW to 4 W, Effective Isotropic Radiated Power (EIRP) is used; it caused a 76.19% reduction in the coverage spacing for TV channels of ECN Network secondary devices. For the White Space Device (WSD) to operate in Temporal mode, the maximum allowable power (4 W) used in spatial mode should be replaced by a 76.19 per cent reduction. Additional sensing margins of 3.76 dB and 4.04 dB for channels 33 and 43 must be added to the FCC threshold limit of-114 dBm criterion for TV white spaces to assure ECN deployment without causing severe interference to TV customers.

Parmi les domaines de l'informatique qui connaissent un regain d'intérêt figurent les systèmes embarqués. Sous cette dénomination, nous classons tous les systèmes mixtes matériel/logiciel autonomes. Les systèmes embarqués font partie intégrante de notre vie de tous les jours sans qu'on en ait toujours conscience. En tant que particulier, ils nous permettent les communications sans fil (téléphonie), nous assistent dans la conduite de nos véhicules, contribuent à notre confort en régulant intelligemment les différents paramètres ...

Even with extended operating hours and relaxing the service-level agreement (SLA), there is significant excess capacity designed into the system * Peak hour orders in peak period exceeds average daily orders in non-peak But what about growth?

Smart industrial processes are impossible without the use of machinery. Majority of these machines comprise rotating machines. As supporting tools for developing maintenance strategies, a Data-driven approach for multifault diagnosis of Rotating Machines is currently used in smart industry. This Chapter presents Multisensor Data Fusion and its application in Predictive maintenance methodology for multifault diagnosis of Industrial Rotating Machines. The main objective of Multisensor Data Fusion, rather than the different sensors being applied independently, are optimally fused to take advantage of their respective strengths, by combining data from multiple sensors and related information to achieve specific inferences than could be achieved by a single sensor. This chapter presents a methodology using data extraction features domain parameters for multifault diagnosis of Rotating Machines. The analysis shows that Root Mean Square Amplitude increases as fault develops, Crest Factor is more for healthy bearing and less for faulty bearing, these can provide early warning of faults

In this paper, two types of cancellation gamma acts was introduced "namely complete cancellation and strong cancellation. Some basic results and characterizations" of these" concepts" are given. Also, the relation between of (complete, strong) cancellation gamma acts and cancellation gamma ideal was discussed. Under the condition of multiplication gamma acts various properties and characterizations of (complete, strong) cancellation gamma acts are considered.

Dynamic opportunistic channel access with software-defined radio at a network layer in distributed cognitive IoT introduces a concurrent channel selection along with end-to-end route selection for application data transmission. State-of-the-art cognitive IoT big data-based routing protocols are not explored in terms of how the spectrum management is being coordinated with the network layer for concurrent channel route selection during end-to-end channel route discovery for data transmission of IoT and big data applications. In this paper, a reactive big data-based “cognitive dynamic source routing protocol” is proposed for cognitive-based IoT networks to concurrently select the channel route at the network layer from source to destination. Experimental results show that the proposed protocol cognitive DSR with concurrent channel route selection criteria is outperformed. This will happen when it is compared with the existing distributed cognitive DSR with independent channel route ap...

In this paper, we propose a comprehensive framework for performance analysis of secure communications over non-small scale fading channels. Considering the three different cases where the main and eavesdropper channels experience independent/correlated log-normal fading, or independent composite fading, we study secrecy capacity and secrecy outage (including the probability of non-zero secrecy capacity and secure outage probability), respectively. The approximated closed-form expressions for secrecy capacity, the probability of non-zero secrecy capacity, and secure outage probability have been derived for these three different types of non-small fading channels, respectively. Finally, the accuracy of our performance analysis is verified by simulation results.

In this paper, we consider a coded cooperative communication network with multiple energy-harvesting (EH) relays. In order to adequately address the problem of error propagation due to the erroneous decoding at the relays, as in the case of conventional decode and forward (DF) relaying protocol, we propose coded cooperative schemes with hard information relaying (HIR) and soft information relaying (SIR) strategies. The performance of the relayed communication with EH relay depends crucially on the channel decoding capability at the relay, channel gains at the source-relay and relay-destination links, and ultimately on the power-splitting ratio of the relay EH receiver. The exact closed-form expression for the outage probability performance of the coded cooperative scheme with HIR strategy and relay selection (CC-HIR-RS) is derived for both cases, namely for constant and optimal power-splitting ratios. Concerning the coded cooperative scheme with SIR strategy, a Rayleigh Gaussian log likelihood ratio-based model is used to describe the soft estimated symbols at the output of the relay soft encoder. Directives are provided to determine the model parameters, and, accordingly, the signal-to-noise ratio (SNR) of the equivalent one-hop relaying channel is derived. A closed-form expression for the outage probability performance of the proposed coded cooperative scheme with SIR and relay selection (CC-SIR-RS) is derived. In addition, a fuzzy logic-based power-splitting scheme in EH relay applying SIR is proposed. The fading coefficients of the source-relay and relay-destination links and distance between source and relay node are considered as input parameters of the fuzzy logic system to obtain an appropriate power-splitting ratio that leads to a quasi-optimal SNR of the equivalent end-to-end channel. Monte Carlo simulations are presented to demonstrate the validity of the analytical results, and a comparison between the performance of the CC-HIR-RS scheme with constant and optimized power-splitting ratios and that of the CC-SIR-RS scheme with constant and fuzzy logic-based power-splitting ratios is provided.

Abstract: This paper describes some of the outcome of the FP7 project PHYDYAS, whose main objective was to propose a new physical layer that will enable introduction of cognitive radios and dynamic access spectrum management. During the project both a software simulator ...

The growing importance of energy-efficient networks capable of handling high data rates
poses a significant concern for network operators. With the evolution of new mobile data network
standards, subscribers have surged and increased demand for high-speed data traffic, enabling
seamless streaming of social media content within seconds. Network operators are tasked with
meeting consumer satisfaction, and to achieve high data rates and good signal quality, they have
adopted the deployment of small cells.
In this research, energy efficiency is enhanced through an investigation of the small cell-controlled
scheme, which is then extended to incorporate a power control strategy based on throughput
measurements. Additionally, energy consumption is reduced by adjusting the transmit power based
on traffic patterns. Specifically, during periods of normal traffic, the power utilization is set at 40% of
the total power, while in times of increased traffic intensity, 60% of the total power is allocated. This
traffic intensity- based power distribution scheme results in a 13-15% increase in energy efficiency
compared to the small cell-controlled sleep mode.
Keywords— small cell, power control, energy efficiency, power distribution.

The idea of ad hoc networking is gaining importance as more and more dynamic routing protocols have been designed and a lot of research with state of the art network traffic simulator has been carried out. Routing protocols solve many problems of ad hoc networks. In this paper we are aiming to provide a performance comparison of three routing protocols i.e. ADV, AODV and DSDV. NCTUns 6.0 is used as a simulator. The performance metrics for evaluating the protocols are number of packet dropped, number of packet collision and throughput.

Pre-processing techniques employed at the transmitter side of multiple-input, multiple-output (MIMO) systems, such as the ones used by MIMO singular value decomposition (SVD) (MIMO-SVD) techniques, can lead to signals with large envelope fluctuations and high peak-to-average power ratio (PAPR). For this reason, we can have amplification difficulties and increased sensitivity to nonlinear distortion effects. In this work, we consider MIMO-SVD schemes with strong nonlinear distortion effects. It is shown that contrarily to what one could expect, the asymptotic optimum performance of the MIMO system with strong nonlinear distortion effects can be much better than the optimum performance with an ideal, linear transmitter. 1

Many studies show that the Dedicated Short Range Communication band is insufficient to carry increasing wireless data traffic in vehicular networks. The release of large TV spectra by FCC for cognitive access provides additional spectrum resources to solve the spectrum scarcity problem. However, FCC allows fixed devices to use high transmitting powers, while requiring portable devices to use significantly lower powers. This power asymmetry policy leads to a challenging coexistence environment for portable (e.g., vehicular) and fixed (e.g., IEEE 802.22) networks. In this paper, we address the coexistence problem between vehicular and 802.22 networks via resource allocation. We show that the problem is an NP-hard mixed-integer nonlinear programming problem, to which we propose two algorithms. First, we convert it to a convex programming problem, and propose a nearoptimal primal-dual algorithm. Next, we reformulate the problem as a packing problem, and present a constantfactor approximation algorithm. Finally, we evaluate the algorithms through numerical examples. 2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

Primary users (PU) separation concerns with the issues of distinguishing and characterizing primary users in cognitive radio (CR) networks. We argue the need for PU separation in the context of collaborative spectrum sensing and monitor selection. In this paper, we model the observations of monitors as boolean OR mixtures of underlying binary latency sources for PUs, and devise a novel binary inference algorithm for PU separation. Simulation results show that without prior knowledge regarding PUs activities, the algorithm achieves high inference accuracy. An interesting implication of the proposed algorithm is the ability to represent n independent binary sources via (correlated) binary vectors of logarithmic length.

The paper reports on an innovative approach to the management of Cognitive Radio Networks (CRNs). As part of achieving this functionality, a new architecture implemented at the application layer is presented. The research challenges for developing a CRN management solution are on addressing, sensing and prediction, routing, decision making and middleware. Cognitive radio networks are expected to address and to solve several important challenges like, e.g., opportunistic spectrum access, spectrum heterogeneity, network heterogeneity and the provision of diverse Quality of Service (QoS) to different applications. Consequently, a number of management functions are necessary to address the associated challenges with the management of CRNs. The paper provides a brief introduction to these components while focusing on the CR routing, addressing and content representation.

Cognitive Radio Networks (CRNs) are emerging as a viable solution for exploiting the available spectrum and solving overcrowding in the operating bands. Several dimensions in the process of identification, management and routing need to be handled to overcome the challenges associated with the management of CRNs. A very important topic in achieving an effective and flexible management solution is related to the data representation of the different CRN dimensions. Scalability, high tolerance to churn and low latencies in accessing the stored data are fundamental characteristics in order to keep up with the dynamic nature of a mobile environment. Accordingly, to achieve a robust data representation that can handle all these requirements in an efficient way we focus our attention on peer-to-peer (P2P) systems. These systems are well known for providing an efficient platform to develop scalable and robust applications. Hence, in this paper we investigate using geometric multi-dimensional data representation and addressing system based on basic CAN functionality. Results obtained in our experiments are reported, providing useful information to improve the resilience to churn of our system.

Cognitive radio networks are expected to address and resolve important operational challenges such as opportunistic spectrum access, spectrum and network heterogeneities and requests for the provision of diverse Quality-of-Service (QoS) for different applications. Accordingly, a number of network functionalities are required to take into account these challenges towards the efficient management of cognitive radio networks. This paper advances a new architecture for the management of cognitive radio networks. The architecture is designed and developed at the application layer and incorporates sensing and prediction, addressing and routing, middleware and decision making. Accordingly, a number of management functions are required to address the challenges associated with the management of cognitive radio networks. The paper provides an analysis of these components as well.

Spectrum is considered one of the most highly regulated and limited natural
resources. Cognitive radio (CR) relies on cutting-edge technology which
helps to rectify the issues related to spectrum shortage in wireless
communication systems. The CR technology allows the secondary user to
accomplish the process related to spectrum sensing for identifying the usage
of spectrum in the cognitive radio network (CRN). Though various spectrum
sensing approaches are introduced, they exhibit complexity during spectrum
sensing. To overcome the issues related to spectrum sensing and utilization,
this research introduces improved quantum inspired evolution (IQISE)
algorithm with ResNet 50 architecture. The IQISE-ResNet 50 which helps to
enhance the spectrum efficiency is used in spectrum sensing. The detection
of occupied and unoccupied users in CRN is performed using ResNet 50
architecture, while the IQISE is utilized in the process of training the model
and optimizing the weights to enhance spectrum sensing efficiency. The
experimental results show that the results achieved by the proposed approach
are more effective than S-QRNN and honey badger remora optimizationbased AlexNet (HBRO-based AlexNet). For example, the probability of
correct classification of the proposed approach at -10 dB for binary phase
shift keying (BPSK) modulation is 0.55, whereas the S-QRNN achieves an
accuracy of 0.49.

The vast rise in the number of Internet-connected devices necessitates a more accessible spectrum. As a result, Cognitive Radio was already proposed as a solution to the problem of restricted spectrum resources by utilizing available spectrum which is assigned to primary users. This method allows the secondary user to utilize the spectrum whenever the primary user is not using it, and it does so without intruding with the primary user. Whenever the secondary user detects the spectrum, it faced some issues, such as complexity in sensing leading to a lack of noise value, and the primary user is hidden to all secondary users. In order to tackle these challenges, an adaptive threshold matched filter detector and a cooperative matched filter detector are utilized in this paper to detect the spectrum. The probability of detection (Pd), probability of miss detection (Pm), and probability of false alarm (Pf) are the metrics used to assess sensing accuracy. To simulate suggested detectors, t...

Cellular communication networks are plagued with redundant capacity, which results in low utilization and costeffectiveness of network capital investments. The redundant capacity can be exploited to deliver secondary traffic that is ultra-elastic and delay-tolerant. In this paper, we propose an analytical framework to study the capacity-delay tradeoff of elastic/secondary traffic in large scale cellular networks with spectrum aggregation. Our framework integrates stochastic geometry and queueing theory models and gives analytical insights into the capacity-delay performance in the interference limited regime. Closed-form results are obtained to characterize the mean delay and delay distribution as functions of per user throughput capacity. The impacts of spectrum aggregation, user and base station (BS) densities, traffic session payload, and primary traffic dynamics on the capacity-delay tradeoff relationship are investigated. The fundamental capacity limit is derived and its scaling behavior is revealed. Our analysis shows the feasibility of providing secondary communication services over cellular networks and highlights some critical design issues.

Cognitive radio (CR) is considered one of the prominent techniques for improving the utilization of the radio spectrum. A CR network (i.e., secondary network) opportunistically shares the radio resources with a licensed network (i.e., primary network). In this work, the spectral-energy efficiency trade-off for CR networks is analyzed at both link and system levels against varying signal-to-noise ratio (SNR) values. At the link level, we analyze the required energy to achieve a specific spectral efficiency for a CR channel under two different types of power constraint in different fading environments. In this aspect, besides the transmit power constraint, interference constraint at the primary receiver (PR) is also considered to protect the PR from a harmful interference. Whereas at the system level, we study the spectral and energy efficiency for a CR network that shares the spectrum with an indoor network. Adopting the extreme-value theory, we are able to derive the average spectral and energy efficiency of the CR network. It is shown that the spectral efficiency depends upon the number of the PRs, the interference threshold, and how far the secondary receivers (SRs) are located. We characterize the impact of the multi-user diversity gain of both kinds of users on the spectral and energy efficiency of the CR network. Our analysis also proves that the interference channels (i.e., channels

Cellular communication networks are plagued with redundant capacity, which results in low utilization and costeffectiveness of network capital investments. The redundant capacity can be exploited to deliver secondary traffic that is ultra-elastic and delay-tolerant. In this paper, we propose an analytical framework to study the capacity-delay tradeoff of elastic/secondary traffic in large scale cellular networks with spectrum aggregation. Our framework integrates stochastic geometry and queueing theory models and gives analytical insights into the capacity-delay performance in the interference limited regime. Closed-form results are obtained to characterize the mean delay and delay distribution as functions of per user throughput capacity. The impacts of spectrum aggregation, user and base station (BS) densities, traffic session payload, and primary traffic dynamics on the capacity-delay tradeoff relationship are investigated. The fundamental capacity limit is derived and its scaling behavior is revealed. Our analysis shows the feasibility of providing secondary communication services over cellular networks and highlights some critical design issues.

Presently the demand for robust wireless communication
with coordinated use of mobile systems and the internet
result in ineffective use of the spectrum, where a
considerable portion of the spectrum is neglected.
Consequently, Cognitive Radio(CR) is innovative
technology that raising the spectrum usage performance.
Spectrum sensing(SS) is an essential aspect in detects
whether vacant channels are in the spectrum and renders
them to secondary users. The cyclostationary spectrum
sensing(CSS) technique is one of the most effective methods
able to efficiently detects unoccupied spectra with low
signal-to-noise ratios(SNR). CSS involves the use of a large
number of samples for detection resulting in high
complexity, cost, and processing time. In this paper, a low
computational complexity CSS approach is proposed based
on using Haar wavelet transform and signed correlator. The
proposed method performance is evaluated over Rayleigh
flat fading and AWGN channels with low SNR values. The
acquired simulation results indicated the proposed method
achieved reduced complexity to about 80%, on a penalty a
very slight reduction in detection probability Pd of about 7%
at SNR equals -25 dB. Then the proposed method is
optimized to reduce the detection probability to 6%, and 2%
through the use of stratified sampling, and BPF respectively.

Nous remercions Dieu, le Tout Puissant, le maître du temps et des circonstances, pour la protection à notre égard tout au long de notre vie. Nos sincères remerciements s'adressent respectivement au Professeur Dr AKWIR NKIEDIEL Alain, et au Msc. Ing. KAMBALE WAMUHINDO qui ont accepté d'être respectivement directeur et encadreur de ce travail. A toutes les autorités académiques de L'ULPGL-GOMA pour l'encadrement et l'instruction durant ces années passées sous leurs surveillances. Toutes nos gratitudes à vous, chers parents Josué KALAMIRE et Régine VASOLENE pour vos sacrifices, vos précieux soutiens et conseils et en qualité des vaillants parents et dignes de notre avenir. Sans votre amour, sans votre tendresse, sans votre affection parentale, et l'oubli de soi, nous ne serions pas ce que nous sommes et ce travail ne serait jamais mise au point. Nous remercions particulièrement le couple Serges KILUMBIRO -Noëlla TABASIMWA pour son amour, ses sacrifices, sa compréhension, ses prières. Son aide nous a été très utile pendant notre parcours. Nous resterons reconnaissant.

Um pequeno panorama da História e da situação atual da audição de peças de rádio arte em emissoras de rádio FM-AM e em webradios no mundo e, em especial, no Brasil. Trata com maior detalhe da criação da rederadioarte, uma rede criada na web para intercambio entre radioartistas do Brasil e alguns de fora, e sua proposta, já em execução, de produção de programas para rádios educativas brasileiras. Palavras-chave: Radioarte. Webradio. Rederadioarte. Rádios educativas.

In service oriented architectures, Quality of Service (QoS) is a key issue. Service requestors evaluate QoS at run time to address their service invocation to the most suitable provider. Thus, QoS has a direct impact on the providers' revenues. However, QoS requirements are difficult to satisfy because of the high variability of Internet workloads. This paper presents a self-managing technique that jointly addresses the resource allocation and admission control optimization problems in virtualized servers. Resource allocation and admission control represent key components of an autonomic infrastructure and are responsible for the fulfillment of service level agreements. Our solution is designed taking into account the provider's revenues, the cost of resource utilization, and customers' QoS requirements, specified in terms of the response time of individual requests. The effectiveness of our joint resource allocation and admission control solution, compared to top performing state-of-the-art techniques, is evaluated using synthetic as well as realistic workloads, for a number of different scenarios of interest. Results show that our solution can satisfy QoS constraints while still yielding a significant gain in terms of profits for the provider, especially under high workload conditions, if compared to the alternative methods. Moreover, it is robust to service time variance, resource usage cost, and workload mispredictions.

A total of 300 samples were collected from suspected patient to find the prevalence of Cutaneous Leishmaniasis as well as Polymerase Chain Reaction (PCR) based identification of respective species in the endemic areas of Dir Lower and Dir Upper (Khyber Pakhtunkhwa Province) Pakistan. These patients including (171) males and (129) females from these areas, irrespective of age, were analyzed using patient’s biopsy samples, slide smears and filter paper impressions from lesions. Kinetoplast kDNA-PCR and (Internal Transcribed Spacer 1(ITS1-PCR) were performed using RV1/RV2 and LITS R/L5.8s primers, respectively. Age group of 0-15 years was found to be the most infected with 47.5% of total cases while age group of 45 years and above showed lowest rate (7.0%). Out of 300 patients, 172 (56.17%) were positive by microscopy, 79.5% (238 Patients) by ITS1-PCR-Assay and 280 (93.5%) were confirmed by kDNA-PCR. It was concluded that cutaneous leishmaniasis in prevalent in local population of Dir ...

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The over dependent and demand for wireless communication network has necessitated efficient and effective spectrum utilization and network optimization. This study proposes an AI-driven Cognitive Radio Networks (CRNs) framework that integrates CRNs and Artificial Intelligence (AI) by leveraging machine learning (ML) and Long Short-Term Memory to optimize spectrum management and overall network performance. The approach involves creating a model that uses AI and machine learning algorithms for dynamic spectrum allocation, capable of adapting to changing network conditions without human intervention. Quantitative results highlight the success of AI-driven CRNs in improving spectrum utilization. AI algorithms improved spectrum allocation efficiency by 20%, reduced interference by 15%, and boosted overall network throughput by 30%. Additionally, the study demonstrates that AI-powered CRNs can maintain network stability even during periods of high traffic, ensuring smooth communication with minimal latency. The research also touches on policy changes regarding spectrum regulation, advocating for more flexible and adaptive approaches to spectrum management. By demonstrating the practical advantages of AI in CRNs, this study contributes to efforts aimed at addressing the gap between limited spectrum availability and the growing demand for wireless connectivity. Ultimately, it offers valuable insights into the future of intelligent, adaptive wireless networks.

This paper 1 deals with spectrum sensing techniques used to efficient utilization of limited spectrum resource. The most used technique is the energy detector as it is the simplest one for real time implementation and performs well for high SNR. This paper is concerned with this well known method and introduces an enhanced energy detector, in order to enhance its performance in low SNR. The proposed detector is based on the algebraic approach used for spike location, to make the detection more robust in a noisy environment. The proposed system model introduces an algebraic preprocessing bloc to attenuate the noise effect and enhance the detector performance at lower SNR. The detection is achieved by a second bloc that implements the conventional energy detection method. Simulation results, performed on DVB-T signals in additive Gaussian noisy context, show that the proposed detector performs much better than the conventional energy detector.

Chapter 1. Prime numbers linearity. Cyclicity of numbers. Chaos of prime numbers. The first part of this chapter is based on an article by [Marek Berezowski, 2023] published and distributed under the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The second part based on article by Marek Berezowski published on the scientific social portals e.q. arXiv.

In a cognitive radio network, a primary user (PU) shares its spectrum with secondary users (SUs) temporally and spatially, while allowing for some interference. We consider the problem of estimating the no-talk region of the PU, i.e., the region outside which SUs may utilize the PU's spectrum regardless of whether the PU is transmitting or not. We propose a distributed boundary estimation algorithm that allows SUs to estimate the boundary of the no-talk region collaboratively through message passing between SUs, and analyze the trade-offs between estimation error, communication cost, setup complexity, throughput and robustness. Simulations suggest that our proposed scheme has better estimation performance and communication cost trade-off compared to several other alternative benchmark methods, and is more robust to SU sensing errors, except when compared to the least squares support vector machine approach, which however incurs a much higher communication cost.

The detection of transmitted data collusion among sensing nodes needs to be resolved at data link layer. It takes a lot algorithm calculation effort and time constraint. A new method to sense the performance of cognitive radio (CR) by avoiding interference based on new master node (MN) algorithm. Interference could be reduced significantly by using only PHY (physical) information of the cognitive radio network. It saves a lot computational on above layer and detect the collusion of transmitted data as early as possible. By using a novel MN algorithm at PHY layer, it reduces the cost of computation and time to detect and avoid collusion of transmitted data.